An efficient algorithm to discover colossal closed itemsets in high dimensional data /
The current trend of data collection involves a small number of observations with a very large number of variables, known as high dimensional data. Mining these data produces an explosive number of smaller item sets which are less important than colossal (large) ones. As the trend in Frequent Itemse...
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| Main Author: | |
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| Format: | Thesis Book |
| Language: | English |
| Published: |
Kuala Lumpur :
Kulliyyah of Engineering, International Islamic University Malaysia,
2020
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| Subjects: | |
| Online Access: | http://studentrepo.iium.edu.my/handle/123456789/11050 |
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